How we can choose test cases effectively in regression?
How early we can make it are we doing it wrong ?
From the context of testing, what are the practical definitions of machine learning, deep learning, and automation -and how might they overlap?
How do you see the role of automation engineers evolving as organizations adopt a more integrated quality approach?
How can reframing our understanding of automation improve the application of it in testing excellence?
What are the most common mistakes organizations make when implementing test automation, and how can they be avoided?
What future trends in test automation should we be aware of, and how can we prepare our teams to adapt to these changes?
What strategies have you found effective in breaking down monolithic test suites into more manageable suites of tests, and what challenges have you encountered in doing so?
How can we effectively communicate the value of automation to non-technical stakeholders?
When can we integrate the new automation testing tools in our daily routine?
When we tie (smoke) tests to the Definition of Done, how do we prevent or alleviate the effect of autotest dev being the bottleneck because the SW functionality is “done” but the autotest isn’t developed or “done”?
Are we ever looking at a post-automation world in testing, and if so, what trends and tools might define it?
Hey there!
From my takeaway, determining which tests to automate starts with assessing the stability and repetitiveness of test cases. Focus on high-impact tests, such as those that are executed frequently or critical to application functionality. Melissa emphasized that automating tests that change often can lead to more maintenance than benefits.
Hope this helps! 
Hi there!
One common mistake is treating automation as a silver bullet. It’s essential to set realistic expectations and not to automate everything at once. As Melissa pointed out, starting with a strategic approach and gradually scaling up can lead to better outcomes.
Hope this clears things up!
Hello!
To ensure you’re automating the right tests, prioritize based on business value and frequency. Melissa suggested evaluating tests regularly and involving team members from different disciplines to identify critical areas for automation.
Hope this helps!
Hey!
To ensure automation saves time, focus on writing clear, maintainable tests and involve team members in the process. As highlighted in the talk, regular reviews of automated tests can help identify any that are burdensome or unnecessary.
Hope this is useful!
Hi there!
One practical approach Melissa shared was to start small with a few high-priority test cases and expand from there. This way, teams can quickly see the value of automation without overwhelming themselves.
Hope this sheds some light!
Hey!
Many believe this due to misconceptions about automation’s capabilities. Melissa discussed how automation can enhance, but not replace, the human touch in testing. Manual testing remains crucial for exploratory and usability aspects.
Hope this clarifies!
Hello!
Poor automation can lead to flaky tests and unreliable outcomes, which in turn affects software quality. Melissa stressed the importance of well-structured tests to maintain reliability and confidence in the automation process.
Hope this helps!
Hi there!
Measuring effectiveness can be done through metrics like reduced testing time, increased test coverage, and fewer bugs in production. Melissa highlighted the importance of tracking these metrics over time to assess ROI.
Hope this is helpful!